| 1. |
- Aguiar-Pulido, Vanessa, et al.
(författare)
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Systems biology analysis of human genomes points to key pathways conferring spina bifida risk
- 2021
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 1091-6490. ; 118:51
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Tidskriftsartikel (refereegranskat)abstract
- Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders.
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| 2. |
- Bekele, Maheteme, et al.
(författare)
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Tumor and immune cell profiling in breast cancer using highly multiplexed imaging mass cytometry single-cell technology demonstrates tumor heterogeneity and immune phenotypic abnormality in Ethiopian women
- 2020
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Ingår i: Cancer Research. - : American Association for Cancer Research. - 0008-5472 .- 1538-7445. ; 80:21 Suppl.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Tumor heterogeneity represents a complex challenge to cancer treatment, disease recurrence, and patient survival. Imaging mass cytometry (IMC) is an emerging proteomic tool for cancer profiling in tumor tissue samples. IMC enables digital image analysis by multiplexed immunostaining of cells and proteins within tissue and preserves spatial relations within tumor environment. We have applied IMC based approach to study the heterogeneity of invasive breast carcinoma protein expression pattern in formalin fixed paraffin embedded tissues.Methods: A total of 10 region of interest (ROI) derived from 5 patients with primary invasive breast carcinoma representing three molecular subclasses (HR+/HER2-,HER2+/HR- and TNBC) were stained with a 30-marker IMC metal labeled antibody panel (α-SMA, EGFR, p53, CD33, CD16, CD163, CD11b, PDL1, CD31, CD45, D44,Vimentin, FoxP3, CD4, ECadherin, CD68, CD20, CD8a, Cytokeratin7, PD1, GranzymeB, Ki67, ColTypeI, CD3, CD45RO, HLADR, DARC & CD11c). Tissue imaging was done by quantifying the abundance of bound antibody with a Hyperion IMC. MCD Viewer was used for visualization purpose and to export raw 16-bit tiff images for segmentation on CellProfiler. Segmentation masks were combined with the individual tiff files to extract single-cell information from each individual image. HistoCAT was applied to perform unbiased clustering of cell populations using the PhenoGraph algorithm and clustered cell populations was overlaid on t-SNE plot. The relative marker expression was used to generate heat-maps and each cluster was manually assigned a phenotype based on its expression profile.Results: The t-SNE generated from each ROI revealed different distinct cell populations and we report the presence of diverse tumor and immune cell populations in our samples. The (min, max) number of PhenoGraph clustered tumor cell populations in HR+/HER2-, HER2+ and TNBC Cases were (5,8) (7,9) and (5,7) respectively. Similarly, the (min, max) number of PhenoGraph clustered immune cell populations in HR+/HER2-, HER2+ and TNBC Cases were (5,8) (7,9) and (5,7) respectively. We also document the presence of inter and intra-tumor heterogeniety in expression of PD1 and PDL1 in all the tumor subtypes studied. Additionally, we report a phenotypic abnormality in the immune cell populations identified with dual or triple markers expression of the canonical CD antigens of T-Cells, B-Cells and macrophages.Conclusion: The current study demonstrates high-dimensional visualization with the simultaneous analysis of epithelial, immune, and stromal components using IMC can be used to explore cell populations in tumor tissue to quantify tumor heterogeneity or identification of novel clustering patterns that has potential for translational research and clinical practice. Significance: This study presents the potential of Imaging Mass Cytometry and single cell analysis algorithms in multiplex high throughput tumor tissue studies.
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| 3. |
- Cuppen, Edwin, et al.
(författare)
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Implementation of Whole-Genome and Transcriptome Sequencing Into Clinical Cancer Care
- 2022
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Ingår i: JCO Precision Oncology. - : American Society of Clinical Oncology. - 2473-4284. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE The combination of whole-genome and transcriptome sequencing (WGTS) is expected to transformdiagnosis and treatment for patients with cancer. WGTS is a comprehensive precision diagnostic test that isstarting to replace the standard of care for oncology molecular testing in health care systems around the world;however, the implementation and widescale adoption of this best-in-class testing is lacking.METHODS Here, we address the barriers in integrating WGTS for cancer diagnostics and treatment selection andanswer questions regarding utility in different cancer types, cost-effectiveness and affordability, and otherpractical considerations for WGTS implementation.RESULTS We review the current studies implementing WGTS in health care systems and provide a synopsis of theclinical evidence and insights into practical considerations for WGTS implementation. We reflect on regulatory,costs, reimbursement, and incidental findings aspects of this test.CONCLUSION WGTS is an appropriate comprehensive clinical test for many tumor types and can replacemultiple, cascade testing approaches currently performed. Decreasing sequencing cost, increasing number ofclinically relevant aberrations and discovery of more complex biomarkers of treatment response, should pave theway for health care systems and laboratories in implementing WGTS into clinical practice, to transform diagnosisand treatment for patients with cancer.
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